American Express Careers
Machine Learning Engineer
- More than 70%+ of the time spent on coding and/or hands-on technical implementation of re-usable frameworks to drive adoption of Machine Learning in the Enterprise
- Leading your own project. Suggesting, collecting and synthesizing requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.
- Architecting, estimating and planning technical solutions to problems
- Implementing new, highly scalable platform components and tools leveraging machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing and Time Series predictions
- Actively participating in team and company-wide architecture and engineering discussions and forums
- Master of Science or higher in a quantitative discipline, e.g. Data Science, Statistics, Mathematics, Computer Sciences or similar Bachelor of Science with 1-2 years of experience in a highly quantitative position
- Firm grip of Python environment and libraries (scikit, nltk, pandas and numpy). Working knowledge of R & Spark is a plus.
- Proven experience of solving complex business problems using Machine Learning techniques like Regression, Classification, Supervised or Unsupervised Recommenders, Deep iterative learning, Neural Nets etc.
- Deep knowledge of Statistics and Maths, and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable.
- Experience of working in Distributed/Cluster computing environment is desirable
- Ability to work in cross functional teams
- Excellent data presentation and visualization skills
- Hands on knowledge of SQL/ Hive QL is desirable
- Demonstrate self-reliance to achieve goals collaboratively
- Must be curious, hardworking and detail-oriented, and motivated by complex analytical problems.
- Thought leadership and innovative thinking
Eligibility to work in US for American Express is required as the company will not be pursuing sponsorship for this position
Tags: CFE-11160, CFE-12820, CFE-12801, CFE-12800
Schedule (Full-Time/Part-Time): Full-time
Date Posted: Jul 12, 2019, 3:47:57 PM